Numerous methods and apparatus have been developed to suppress or remove noise from information-bearing signals. A well-known noise suppression method uses a noise estimate obtained using a calculation of a minimum mean square error or “MMSE.” MMSE is described in the literature. See for example Alan V. Oppenheim and George C. Verghese, “Estimation With Minimum Mean Square Error,” MIT Open CourseWare, http://ocw.mit.edu, last modified, Spring, 2010, the content of which is incorporated herein by reference in it is entirety.
While Log-MMSE is an established noise suppression methodology, improvements have been made to it over time. One improvement is the use of the speech probability presence or “SPP” as an exponent to the log-MMSE estimator, {circumflex over (q)} which is also known as the optimal log-spectral amplitude based estimator or “OLSA” approach, which makes the MMSE algorithm effectively reach its maximum allowed amount of attenuation.
The OLSA modification of the Log-MMSE noise estimation suffers from two known problems. One problem is that it increases so called musical noise in low signal-to-noise ratio situations. Another and more significant problem is that it also over-suppresses weak speech in noisy conditions. An MMSE-based noise estimation that reduces or avoids the problems known to exist with the prior art, OLSE modification of an MMSE-based noise estimate determination would be an improvement over the prior art.